Text Image Compression Using Soft Pattern Matching

نویسنده

  • Paul G. Howard
چکیده

We present a method for both lossless and lossy compression of bi-level images that consist mostly of printed or typed text. The key feature of the method is soft pattern matching, a way of making use of the information in previously encountered characters without risking the introduction of character substitution errors. We can obtain lossless compression which is about 20% better than that of the JBIG standard by direct application of this method. By allowing some loss based partly on the pattern matching using a technique called selective pixel reversal, we can obtain compression ratios about 2–4 times the compression ratios of JBIG and 3–8 times those of G3 facsimile with no visible loss of quality. If used in facsimile machines, these compression improvements would translate directly into communication cost reductions of the same factors, or into the capability of transmitting images at higher resolution with no increase in the number of bits sent.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Compressed Pattern Matching for Text

The amount of information that we are dealing with today is being generated at an everincreasing rate. On one hand, data compression is needed to efficiently store, organize the data and transport the data over the limited-bandwidth network. On the other hand, efficient information retrieval is needed to speedily find the relevant information from this huge mass of data using available resource...

متن کامل

Dictionary design for text image compression with JBIG2

The JBIG2 standard for lossy and lossless bi-level image coding is a very flexible encoding strategy based on pattern matching techniques. This paper addresses the problem of compressing text images with JBIG2. For text image compression, JBIG2 allows two encoding strategies: SPM and PM&S. We compare in detail the lossless and lossy coding performance using the SPM-based and PM&S-based JBIG2, i...

متن کامل

Correction to "lossless, near-lossless, and refinement coding of bilevel images"

We present general and unified algorithms for lossy/lossless coding of bilevel images. The compression is realized by applying arithmetic coding to conditional probabilities. As in the current JBIG standard the conditioning may be specified by a template. For better compression, the more general free tree may be used. Loss may be introduced in a preprocess on the encoding side to increase compr...

متن کامل

Compressed Pattern Matching for Predictive Lossless Image Encoding

Pattern matching in compressed image domain is a new topic in computer science. Many works have been reported for pattern matching for compressed text and for lossy compressed image. However, searching of images in lossless compressed domain is almost a blank area and needs to be explored. Lossless image compression is widely used in areas such as medical images, satellite images, geometric ima...

متن کامل

Pattern Matching Machine for Text Compressed Using Finite State Model

The classical pattern matching problem is to nd all occurrences of patterns in a text. In many practical cases, since the text is very large and stored in the secondary storage, most of the time for the pattern matching is dominated by data transmission of the text. Therefore the text compression can speed-up the pattern matching. In this framework it is required to develop an e cient pattern m...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Comput. J.

دوره 40  شماره 

صفحات  -

تاریخ انتشار 1997